Name
Abstract | ||
|---|---|---|
Recommendation services capture and exploit personal information such as demographic attributes, preferences, and user behaviors on the internet. It is known that some users feel uneasiness regarding such information acquisition by systems and have concern over their online privacy. Investigating the structure of the uneasiness and evaluating the effect to user acceptance of the recommender systems is an important issue to develop user-accepting services. In this study, we developed an acceptance model of recommender systems based on a large-scale internet survey using 60 kinds of pseudo-services. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-28509-7_39 | UMAP Workshops |
Keywords | Field | DocType |
acceptance model,online privacy,important issue,demographic attribute,recommender system,user behavior,large-scale internet survey,personal information,user acceptance,information acquisition,recommender systems,privacy | Recommender system,World Wide Web,Internet privacy,Computer science,Information acquisition,Exploit,Personally identifiable information,The Internet | Conference |
Citations | PageRank | References |
2 | 0.42 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hideki Asoh | 1 | 705 | 89.85 |
| Chihiro Ono | 2 | 148 | 15.31 |
| Yukiko Habu | 3 | 2 | 0.42 |
| Haruo Takasaki | 4 | 9 | 2.19 |
| Takeshi Takenaka | 5 | 20 | 6.56 |
| Yoichi Motomura | 6 | 312 | 40.26 |